Forecasting international tourist arrivals in South Korea: a deep learning approach
Siyu Zhang,
Ze Lin,
Wii-Joo Yhang
Abstract:Purpose
This study aims to develop a robust long short-term memory (LSTM)-based forecasting model for daily international tourist arrivals at Incheon International Airport (ICN), incorporating multiple predictors including exchange rates, West Texas Intermediate (WTI) oil prices, Korea composite stock price index data and new COVID-19 cases. By leveraging deep learning techniques and diverse data sets, the research seeks to enhance the accuracy and reliability of tourism demand predictions, contributing signif… Show more
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